Autonomous Vehicle Calibration via Linear Optimization

Abstract: In navigation activities, kinematic parameters of a mobile vehicle play a significant role. Odometry is most commonly used for dead reckoning. However, the unrestricted accumulation of errors is a disadvantage using this method. As a result, it is necessary to calibrate odometry parameters to minimize the error accumulation. This paper presents a pipeline based on sequential least square programming to minimize the relative position displacement of an arbitrary landmark in consecutive time steps of a kinematic vehicle model by calibrating the parameters of applied model. Results showed that the developed pipeline produced accurate results with small datasets.

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@inproceedings{Novotny2022,
  author    = {Georg Novotny and Yuzhou Liu and Wilfried W{\"o}ber and Cristina Olaverri-Monreal},
  doi       = {10.1109/IV51971.2022.9827109},
  isbn      = {9781665488211},
  journal   = {IEEE Intelligent Vehicles Symposium, Proceedings},
  pages     = {527-532},
  publisher = {Institute of Electrical and Electronics Engineers Inc.},
  title     = {Autonomous Vehicle Calibration via Linear Optimization},
  volume    = {2022-June},
  year      = {2022}
}

Recommended citation: Novotny, G., Liu, Y., Wober, W., & Olaverri-Monreal, C. (2022). Autonomous Vehicle Calibration via Linear Optimization. IEEE Intelligent Vehicles Symposium, Proceedings, 2022-June, 527–532. https://doi.org/10.1109/IV51971.2022.9827109